The present work establishes and validates HILIC strategies simple, accurate, exact and precise in pure form and inpharmaceutical dosage for separating and determining theophylline. These methods are developed on HILIC theophyllineseparation in columns ZIC2 and ZIC3. The eluent was prepared by mixing buffer (20% sodium acetate-40 mM, pH 5.5), 80%acetonitrile. The flow rate is 0.8 mL/min, with gradient elution and UV detection at 270 nm. In the ZIC2 and ZIC3 columns oftheophylline determining, the concentration range was 0.01-4μg.ml-1. The lower limit of detection and quantification fortheophylline were determined as 0.130, 0.190 μg.ml-1 and accuracy were 99.70%, 99.58% on ZIC2 and ZIC3, respectively. TheHILIC methods developed and validat

Background: Radiologic evaluation of breast lesions is being achieved through several imaging modalities. Mammography has an established role in breast cancer screening and diagnosis. Still however, it shows some limitations particulary in dense breast.

Methods : Magnetic resonance imaging is an attractive tool for the diagnosis of breast tumors¹ and the use of magnetic resonance imaging of the breast is rapidly increasing as this technique becomes more widely available.¹ As an adjunct to mammography and ultrasound, MRI can be a valuable addition to the work-up of a breast abnormality. MRI has the advantages of providing a three-dimensional view of the breast, performing wit

This study was conducted to know the effect of some phenotype characteristics of corn plant on infection by (CSB), using 13 genotypes of corn plant, planting during autumn season 1997 and 1998. The result revealed that the mean of plant height (with male flowering) was (183-219) cm, the mean of leaf No./ plant in all genotypes was (16-18) leaf but the leaf area of plant was (4350-6249) cm2, there were significant differences of phenotype characteristics between genotypes ,the percentage of infection by (CSB) was (5.9-35.9),% the result showed that the phenotype characteristics had non effect on the infection percentage by (CSB) and the correlation coefficient was not significant.

The porosity of materials is important in many applications, products and processes, such as electrochemical devices (electrodes, separator, active components in batteries), porous thin film, ceramics, soils, construction materials, ..etc. This can be characterized in many different methods, and the most important methods for industrial purposes are the N2 gas adsorption and mercury porosimetry. In the present paper, both of these techniques have been used to characterize some of Iraqi natural raw materials deposits. These are Glass Sand, Standard Sand, Flint Clay and Bentonite. Data from both analyses on the different types of natural raw materials deposits are critically examined and discussed. The results of specific surface are

In the 1970s, the world knew the long-tailed nesokia Nesokia bunnii (Khajuria, 1981) (Rodentia, Muridae) from the Mesopotamian marshes of Garden of Eden in Southern Iraq. This distinct rodent was known from only five voucher specimens collected at the confluence of Tigris and Euphrates Rivers in southern Iraq while its occurrence in Southwestern Iran had
never been reported. In the 1990s, a large extent of its natural habitat was catastrophically desiccated and the animal was last seen in the 1970s. Since then, the status of this elusive rodent was shrouded in mystery. In 2007, an extraordinary photograph of a carcass of this species came to the light from Hawizeh Marsh which was interpreted as concrete evidence of the species’ pers

The normalized difference vegetation index (NDVI) is an effective graphical indicator that can be used to analyze remote sensing measurements using a space platform, in order to investigate the trend of the live green vegetation in the observed target. In this research, the change detection of vegetation in Babylon city was done by tracing the NDVI factor for temporal Landsat satellite images. These images were used and utilized in two different terms: in March 19th in 2015 and March 5th in 2020. The Arc-GIS program ver. 10.7 was adopted to analyze the collected data. The final results indicate a spatial variation in the (NDVI), where it increases from (1666.91 𝑘𝑚2) in 2015 to (1697.01 𝑘𝑚2)) in 2020 between the t